Abstract The men and women involved in the rescue and recovery efforts following the events of September 11, 2001 were exposed to extraordinarily hazardous working conditions and toxic agents. The National Institute of Occupational Safety and Health (NIOSH) and the Centers for Disease Control and Prevention (CDC) implemented the World Trade Center Health Program (WTCHP), which provides health surveillance to monitor and treat WTC-related health consequences among rescue/recovery workers involved in the emergency response and cleanup. Upon enrollment into the program, all responders completed a battery of self- and interviewer-administered questionnaires and scales. Continued follow-up monitors changes in health status and indicates significant long term medical and psychological effects among first responders, including post-traumatic stress disorder (PTSD), gastroesophageal reflux disease (GERD), respiratory outcomes (i.e., asthma) and all cancers. Recent evidence suggest emerging health outcomes including diabetes, headaches, and hearing loss/problems. Despite strong links between WTC exposure and disease outcomes, factors associated with the heterogeneity of disease development and trajectory remain largely unexplained. While several studies of WTC- associated diseases have examined risk and protective factors associated with disease development and trajectory, these studies are limited to a small number of WTC-associated exposure variables (i.e., presence/absence in the dust/debris cloud, working more than 90 days at the site, time at arrived to Ground Zero, etc.) selected a priori based on the disease. Potential protective factors previously examined include education, family and work support. The richness and breadth of the information on potential risk and protective factors in the WTC surveillance dataset is largely untapped. In this proposal, we refer to this mixture of WTC- related risk and protective factors as the ?WTC exposome? and adopt a data-driven approach to examine associations with WTC related health outcomes. We focus on posttraumatic stress disorder, gastroesophageal reflux, respiratory outcomes and all cancers. This proposal addresses a critical gap in our understanding of risk and protective factors for WTC-related diseases by leveraging generalized weighted quantile sum (gWQS) regression, a statistical approach designed to examine associations between a mixture of correlated factors and a health outcome. Using gWQS, we will create a weighted index representing the totality of characteristics described in the WTC-surveillance dataset and examine a) how the overall index (or ?mixture?) is associated with the incidence of WTC-related disease and b) determine which of the baseline factors are most strongly associated with the outcome and the direction of those associations (i.e., increase the risk for disease vs. protect against the risk for disease). Application of this approach could be expanded to understand risk and resilience to other WTC-associated diseases. Ultimately, this will better identify responders at risk to developing adverse outcomes and identify factors that may protect against the development or progression of disease.